Welcome to the Neuro-Rehabilitation Engineering Laboratory

in the Department of Mechanical Engineering at KAIST.

Our mission is to improve quality of life of those who suffer from physical impairments due to injuries. We apply engineering principles to enhance the effectiveness of rehabilitation after injuries and to improve reliability and accuracy of clinical assessments to be able to provide optimized rehabilitation programs. We also try to understand the mechanism of recovery to suggest optimal rehabilitation program after injuries. These research themes not only improve quality of lives of patients and disabled people but also will contribute to build better healthcare systems for ourselves who will live in the upcoming aged society.

Assessment Robotics

Development of Haptic Training Tools for Objective Assessment.

In rehabilitation medicine, most assessments still depend on subjective perception of clinicians. The subjectivity degrades reliability of the assessment scales. For reliable assessment, we developed robotic devices which provide haptic simulation of patients for repeatable and objective training of assessment. We also developed haptic models of spasticity, one of the most prevalent impairments, and implemented the models to the simulator. Novice clinicians can be familiarized with the clinical assessment scales through practices using the simulator.

 

Robotics for Hand Manipulation

Soft Hand Exotendon Device providing dexterous motions

Hand is the most affected body part in the upper limb caused by neurological disorders, and the recovery is known to require most time. We are developing a soft hand exotendon device that replicates the structure and function of the hand tendons and muscles to provide dexterous motions with a compact and light design. Repetitive training of various grasping task will be available by using this device, which is expected to improve the recovery of hand functions for activities of daily living.

 

Exoskeleton for Upper Limb

Shoulder disorders became more prevalent in recent years due to the increase in injuries in sports as well as neurological disorders. The patients suffering from the shoulder injuries don’t use the damaged side, so they deteriorate over time. Also, the shoulder joint is the most complex joint in the human body. If the movement of the shoulder joint is not considered, they feel uncomfortable force from the device. The shoulder rehabilitation robot is a low-end shoulder rehabilitation system using only one actuator and passive shoulder joint tracker.  It provies various rehabilitation motion and treatment modes for the patients. The system also includes interesting games.

 

Home-Based Exercise Monitored by Artificial Intelligence for Rehabilitation

This project aims on detecting the rehabilitation exercise motion for shoulder patient during home rehabilitation exercise. Home exercise is essential for the success of rehabilitation treatment. To carry out the purpose, we used IMU sensor signal and various IT technology such as network programming, database and android(java) programming. By cooperating with rehabilitation hospital, patient’s exercise data are obtained and transmitted to the database. Based on the clinical data, deep learning algorithm detect and classify various shoulder exercise and save it as clinical information.

 

VR-based Gait Rehabilitation

Treadmill training is widely used for patients with gait disorder because it provides comfortable and safe environment. By providing a virtual reality for gait rehabilitation, the patients can walk curve as well as straight. In addition, patient can not only be actively participated in training by carrying out the task but also be motivated to training using game provided by VR. Furthermore, we are monitoring the brain activation during gait training using EEG to evaluate the effect of the system.

 

 

Thomas C Bulea, Jonghyun Kim, Diane L Damiano, Christopher J Stanley, Hyung-Soon Park
“Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking”
Frontiers in human neuroscience, 2015 , ,Vol. 9No. 0 ,pp. 0 ~ 0(SCIE, 0:0.0

Dokyeong Ha, Min Song, Hyung-Soon Park
Development of Finger Robot for Simulating Fingers with Contracture and Spasticity
Journal of Rehabilitation Welfare Engineering & Assistive Technology, 2014 , ,Vol. 8No. 4 ,pp. 233 ~ 238(SCIE, 0:0.0

Jonghyun Kim, Hyung-Soon Park, Diane L Damiano,
“An interactive treadmill under a novel control scheme for simulating overground walking by reducing anomalous force”
Mechatronics, IEEE/ASME Transactions on, 2015-06 , ,Vol. 20No. 3 ,pp. 1491 ~ 1496(SCIE, 0:0.0